Exponential stability criteria for fuzzy bidirectional associative memory Cohen-Grossberg neural networks with mixed delays and impulses

被引：8

作者：

He, Weina ^{[1
]}

Chu, Longxian ^{[1
]}

机构：

[1] Pingdingshan Univ, Software Coll, Pingdingshan 467000, Peoples R China

来源：

ADVANCES IN DIFFERENCE EQUATIONS | 2017年

关键词：

fuzzy BAM Cohen-Grossberg neural networks; exponential stability; mixed delays; periodic solution; impulse; GLOBAL ASYMPTOTIC STABILITY; NEUTRAL-TYPE; PERIODIC-SOLUTION; DISTRIBUTED DELAYS; EXISTENCE;

D O I：

10.1186/s13662-017-1082-9

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper is concerned with fuzzy bidirectional associative memory (BAM) Cohen-Grossberg neural networks with mixed delays and impulses. By constructing an appropriate Lyapunov function and a new differential inequality, we obtain some sufficient conditions which ensure the existence and global exponential stability of a periodic solution of the model. The results in this paper extend and complement the previous publications. An example is given to illustrate the effectiveness of our obtained results.

引用

页数：16

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